Semi-supervised learning towards automated segmentation of PET images with limited annotations: Application to lymphoma patients

The time-consuming task of manual segmentation challenges routine systematic quantification of disease burden. Convolutional neural networks (CNNs) hold significant promise to reliably identify locations and boundaries of tumors from PET scans. We aimed to leverage the need for annotated data via semi-supervised approaches, with application to PET images of diffuse large B-cell lymphoma (DLBCL) and primary mediastinal large B-cell lymphoma (PMBCL). We analyzed 18F-FDG PET images of 292 patients with PMBCL (n=104) and DLBCL (n=188) (n=232 for training and validation, and n=60 for external testing). We employed FCM and MS losses for training a 3D U-Net with different levels of supervision: i) fully supervised methods with labeled FCM (LFCM) as well as Unified focal and Dice loss functions, ii) unsupervised methods with Robust FCM (RFCM) and Mumford-Shah (MS) loss functions, and iii) Semi-supervised methods based on FCM (RFCM+LFCM), as well as MS loss in combination with supervised Dice loss (MS+Dice). Unified loss function yielded higher Dice score (mean +/- standard deviation (SD)) (0.73 +/- 0.03; 95% CI, 0.67-0.8) compared to Dice loss (p-value<0.01). Semi-supervised (RFCM+alpha*LFCM) with alpha=0.3 showed the best performance, with a Dice score of 0.69 +/- 0.03 (95% CI, 0.45-0.77) outperforming (MS+alpha*Dice) for any supervision level (any alpha) (p<0.01). The best performer among (MS+alpha*Dice) semi-supervised approaches with alpha=0.2 showed a Dice score of 0.60 +/- 0.08 (95% CI, 0.44-0.76) compared to another supervision level in this semi-supervised approach (p<0.01). Semi-supervised learning via FCM loss (RFCM+alpha*LFCM) showed improved performance compared to supervised approaches. Considering the time-consuming nature of expert manual delineations and intra-observer variabilities, semi-supervised approaches have significant potential for automated segmentation workflows

Evaluation of the effect of prospective biomarker testing on progression-free survival in diffuse large B-cell lymphoma.

Novel treatment regimens combining chemotherapy with targeted agents are being developed for diffuse large B-cell lymphoma (DLBCL). These regimens are expected to show efficacy in biomarker-defined..

A prognostic model integrating PET-derived metrics and image texture analyses with clinical risk factors from GOYA

Image texture analysis (radiomics) uses radiographic images to quantify characteristics that may identify tumour heterogeneity and associated patient outcomes. Using fluoro‐deoxy‐glucose positron emission tomography/computed tomography (FDG‐PET/CT)‐derived data, including quantitative metrics, image texture analysis and other clinical risk factors, we aimed to develop a prognostic model that predicts survival in patients with previously untreated diffuse large B‐cell lymphoma (DLBCL) from GOYA (NCT01287741). Image texture features and clinical risk factors were combined into a random forest model and compared with the international prognostic index (IPI) for DLBCL based on progression‐free survival (PFS) and overall survival (OS) predictions. Baseline FDG‐PET scans were available for 1263 patients, 832 patients of these were cell‐of‐origin (COO)‐evaluable. Patients were stratified by IPI or radiomics features plus clinical risk factors into low‐, intermediate‐ and high‐risk groups. The random forest model with COO subgroups identified a clearer high‐risk population (45% 2‐year PFS [95% confidence interval (CI) 40%–52%]; 65% 2‐year OS [95% CI 59%–71%]) than the IPI (58% 2‐year PFS [95% CI 50%–67%]; 69% 2‐year OS [95% CI 62%–77%]). This study confirms that standard clinical risk factors can be combined with PET‐derived image texture features to provide an improved prognostic model predicting survival in untreated DLBCL

Total metabolic tumor volume as a survival predictor for patients with diffuse large B-cell lymphoma in the GOYA study

This retrospective analysis of the phase III GOYA study investigated the prognostic value of baseline metabolic tumor volume parameters and maximum standardized uptake values for overall and progression-free survival (PFS) in treatment-naïve diffuse large B-cell lymphoma. Baseline total metabolic tumor volume (determined for tumors >1 mL using a threshold of 1.5 times the mean liver standardized uptake value +2 standard deviations), total lesion glycolysis, and maximum standardized uptake value positron emission tomography data were dichotomized based on receiver operating characteristic analysis and divided into quartiles by baseline population distribution. Of 1,418 enrolled patients, 1,305 had a baseline positron emission tomography scan with detectable lesions. Optimal cut-offs were 366 cm3 for total metabolic tumor volume and 3,004 g for total lesion glycolysis. High total metabolic tumor volume and total lesion glycolysis predicted poorer PFS, with associations retained after adjustment for baseline and disease characteristics (high total metabolic tumor volume hazard ratio: 1.71, 95% confidence interval [CI]: 1.352.18; total lesion glycolysis hazard ratio: 1.46; 95% CI: 1.15-1.86). Total metabolic tumor volume was prognostic for PFS in subgroups with International Prognostic Index scores 0-2 and 3-5, and those with different cell-of-origin subtypes. Maximum standardized uptake value had no prognostic value in this setting. High total metabolic tumor volume associated with high International Prognostic Index or non-germinal center B-cell classification identified the highest-risk cohort for unfavorable prognosis. In conclusion, baseline total metabolic tumor volume and total lesion glycolysis are independent predictors of PFS in patients with diffuse large B-cell lymphoma after first-line immunochemotherapy

End-of-treatment PET/CT predicts PFS and OS in DLBCL after first-line treatment: results from GOYA

GOYA was a randomized phase 3 study comparing obinutuzumab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) vs standard-of-care rituximab plus CHOP in patients with previously untreated diffuse large B-cell lymphoma (DLBCL). This retrospective analysis of GOYA aimed to assess the association between progression-free survival (PFS) and overall survival (OS) with positron emission tomography (PET)-based complete response (CR) status. Overall, 1418 patients were randomly assigned to receive 8 21-day cycles of obinutuzumab (n 5 706) or rituximab (n 5 712) plus 6 or 8 cycles of CHOP. Patients received a mandatory fluoro-2-deoxy-D-glucose-PET/computed tomography scan at baseline and end of treatment. After a median follow-up of 29 months, the numbers of independent review committee-assessed PFS and OS events in the entire cohort were 416 (29.3%) and 252 (17.8%), respectively. End-of-treatment PET CR was highly prognostic for PFS and OS according to Lugano 2014 criteria (PFS: hazard ratio [HR], 0.26; 95% confidence interval [CI], 0.19-0.38; P , .0001; OS: HR, 0.12; 95% CI, 0.08-0.17; P , .0001), irrespective of international prognostic index score and cell of origin. In conclusion, the results from this prospectively acquired large cohort corroborated previously published data from smaller sample sizes showing that end-of-treatment PET CR is an independent predictor of PFS and OS and a promising prognostic marker in DLBCL. Long-term survival analysis confirmed the robustness of these data over time. Additional meta-analyses including other prospective studies are necessary to support the substitution of PET CR for PFS as an effective and practical surrogate end point

Obinutuzumab in hematologic malignancies: Lessons learned to date

AbstractThe routine use of anti-CD20 monoclonal antibodies (mAbs) has improved patient outcomes in CD20-positive non-Hodgkin’s lymphoma (NHL) and chronic lymphocytic leukemia (CLL). Despite the clinical success achieved with rituximab, relapses are still common with further improvements in anti-CD20 mAb efficacy required. Many novel anti-CD20 antibodies are in development, but obinutuzumab is currently the only type II glycoengineered anti-CD20 mAb in clinical testing.Obinutuzumab has increased antibody-dependent cell-mediated cytotoxicity, reduced complement-dependent cytotoxicity and enhanced direct non-apoptotic cell death. In preclinical models, obinutuzumab induced superior tumor remission compared with rituximab at the equivalent dose levels, and was active in rituximab-refractory tumors. Obinutuzumab exhibits encouraging efficacy as monotherapy in NHL, and combined with chemotherapy in relapsed/refractory NHL and treatment-naïve symptomatic CLL. In a recent randomized, phase III trial in patients with untreated comorbid CLL, overall response rate was significantly greater (78% vs. 65%, P<0.0001) and median progression-free survival was significantly prolonged (26.7 vs. 15.2months, P<0.0001) for obinutuzumab plus chlorambucil vs. rituximab plus chlorambucil.Obinutuzumab is a type II anti-CD20 antibody that utilizes distinct mechanisms of action relative to type I antibodies like rituximab and has led to significant clinical improvement over rituximab in a phase III trial in CLL. Further trials are ongoing to determine whether such improvements in outcome will be seen in CD20-positive B-cell malignancies

Health-related quality of life and symptoms in patients with rituximab-refractory indolent non-Hodgkin lymphoma treated in the phase III GADOLIN study with obinutuzumab plus bendamustine versus bendamustine alone

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Prognostic Significance of MYC Rearrangement and Translocation Partner in Diffuse Large B-Cell Lymphoma : A Study by the Lunenburg Lymphoma Biomarker Consortium

PURPOSE: MYC rearrangement (MYC-R) occurs in approximately 10% of diffuse large B-cell lymphomas (DLBCLs) and has been associated with poor prognosis in many studies. The impact of MYC-R on prognosis may be influenced by the MYC partner gene (immunoglobulin [IG] or a non-IG gene). We evaluated a large cohort of patients through the Lunenburg Lymphoma Biomarker Consortium to validate the prognostic significance of MYC-R (single-, double-, and triple-hit status) in DLBCL within the context of the MYC partner gene. METHODS: The study cohort included patients with histologically confirmed DLBCL morphology derived from large prospective trials and patient registries in Europe and North America who were uniformly treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone therapy or the like. Fluorescence in situ hybridization for the MYC, BCL2, BCL6, and IG heavy and light chain loci was used, and results were correlated with clinical outcomes. RESULTS: A total of 5,117 patients were identified of whom 2,383 (47%) had biopsy material available to assess for MYC-R. MYC-R was present in 264 (11%) of 2,383 patients and was associated with a significantly shorter progression-free and overall survival, with a strong time-dependent effect within the first 24 months after diagnosis. The adverse prognostic impact of MYC-R was only evident in patients with a concurrent rearrangement of BCL2 and/or BCL6 and an IG partner (hazard ratio, 2.4; 95% CI, 1.6 to 3.6; P < .001). CONCLUSION: The negative prognostic impact of MYC-R in DLBCL is largely observed in patients with MYC double hit/triple-hit disease in which MYC is translocated to an IG partner, and this effect is restricted to the first 2 years after diagnosis. Our results suggest that diagnostic strategies should be adopted to identify this high-risk cohort, and risk-adjusted therapeutic approaches should be refined further